Dr Natalie Karavarsamis
Data Scientist, Academic Researcher, Lecturer, Consultant

@nataliekarav
n.karavarsamis@latrobe.edu.au
nkarav@unimelb.edu.au

Curriculum Vitae: Link for download.

Lecturer
Department of Mathematics and Statistics
La Trobe University
Melbourne, Victoria, Australia

Honorary Research Fellow
School of Mathematics and Statistics
University of Melbourne
Victoria, Australia


Roles


Announcements


My Events

2019

2018 and earlier


Brief Bio

I am an academic researcher, data scientist, lecturer and consultant. My current roles are: Lecturer in Statistics and Data Science at Department of Mathematics and Statistics, La Trobe University; Honorary Research Fellow at School of Mathematics and Statistics, University of Melbourne; Technical sub-editor at the Australian and New Zealand Journal of Statistics; Reviewer on several international journals; Local Science Organising Committee for ISEC-2020.
I obtained my PhD in Statistics from the School of Mathematics and Statistics, University of Melbourne.

I have extensive industry and consulting experience, for example, Biostatistician and consultant at Centre of Epidemiology at the Cancer Council of Victoria, Biometrician and consultant at Department of Primary Industries, Statistician at School of Medicine (University of Crete, Greece).

Previous academic roles comprise Lecturer at School of Mathematics and Statistics (University of Melbourne), Postdoctoral Research Fellow at School of Biosciences (University of Melbourne) and with School of Mathematical Sciences (RMIT), and Research Fellow at Department of Food and Land Sciences (prior to PhD) (University of Melbourne).

Current research collaborators are Boston Children’s Hospital at Harvard University (USA), Statify at INRIA University of Caen (France), La Trobe University (Australia) and University of Melbourne (Australia).

My research interests include statistical ecology, analysis and modelling of large biological data, genetic data, medical statistics, finance, and others.

I develop methods, models and software for modern statistical approaches for occupancy data using partial, conditional and composite likelihoods, GLMs and GAMs, IWLS. My R software is available for selected methods.
As well, analysis and development of models for large time-series biological data, using functional analysis, machine learning, data mining, HMMs and models for cylindrical distributions. With applications in epilepsy neuroscience and neuroepigenetic research at Harvard University.


Supervision

Available for Honours, Masters and PhD.
* PhD Statistics - Co-supervisor (2018–)
* AMSI Summer Scholars - Supervisor, two scholars (2019)


Grants & Awards (selected)

2018 Australian-French Association for Research and Innovation (AFRAN).

2016– Early Researcher Establishment Grant, School of Mathematics and Statistics, University of Melbourne.


Press & Gallery

2018 AMSI Choose Maths Day, La Trobe